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Tier-1 brand, popular mid-level data-engineer title, and metro hiring increase competition.
Core ETL, Spark, Snowflake and Databricks skills are highly transferable across industries.
Explicit 3+ years and mandatory Snowflake/Databricks/Airflow/Azure skills increase filter rigidity.
Design, develop, test, and performance tune complex ETL pipelines and automation using technologies including Databricks, Snowflake, Spark, Airflow, and SQL.
Manage cloud infrastructure and resolve issues to ensure operational continuity, scheduling data pipelines using Airflow with proper job dependencies.
Deploy code to higher environments (stage/prod) using GitOps tools like GitHub Actions and Jenkins and provide production support for data warehouse solutions.
Bachelor's or master's degree in Computer Science, IT, or related field (B.E./B.Tech./MCA/Graduation).
Minimum 3 years of experience designing and developing ETL solutions in Data Warehouse/BI environments.
Strong technical skills in Snowflake, Databricks, SQL, Hive, Spark, Airflow, and experience working in cloud environments (preferably Azure).
Familiarity with CI/CD pipelines (Jenkins, GitHub Actions) and Agile/Scrum development methodologies.
Experienced in building scalable, automated ETL data pipelines in cloud and big data environments with strong technical ownership.
Comfortable collaborating across technical and non-technical teams, and managing production support tasks.
Preferably has exposure to healthcare domain data or similar regulated environments for domain understanding.